Authorship attribution for Differences between Literary Texts by Bilingual Russian-French and Non-Bilingual French Authors
This work addresses authorship attribution for literary analysis, focusing on bilingual authors, but it appears incremental as it applies standard methods to a new dataset without major methodological innovations.
The paper tackles the problem of identifying common stylistic traits and distinguishing between bilingual Russian-French and non-bilingual French authors using authorship attribution methods, finding that these methods can effectively differentiate between the groups and observe interference phenomena in the texts.
Do bilingual Russian-French authors of the end of the twentieth century such as Andreï Makine, Valéry Afanassiev, Vladimir Fédorovski, Iegor Gran, Luba Jurgenson have common stylistic traits in the novels they wrote in French? Can we distinguish between them and non-bilingual French writers' texts? Is the phenomenon of interference observable in French texts of Russian authors? This paper applies authorship attribution methods including Support Vector Machine (SVM), $K$-Nearest Neighbors (KNN), Ridge classification, and Neural Network to answer these questions.